The popularity of computer and network technologies has been rapidly growing for the past two decades; however, it has been accompanied by a steady growth in cybercrime, which ranges from relatively harmless cases, such as distribution of unsolicited e-mail, commonly known as spam, to more serious cases of cybercrimes, such as denial of service attacks, stealing of confidential financial information, and even cyber warfare and terrorism. It has become obvious that it is imperative to aggressively combat cybercrime. And, one of the most commonly used means for protecting computers from cyber attacks is antivirus software. However, current generation of antivirus software solutions has shortcomings.
Typical antivirus applications can perform several different malware detection methods, generally ranging from relatively quick signature matching to more complex heuristic analysis and emulation. The latter antivirus checking methods are generally resource intensive, which has detrimental effect on the productivity of computers on which they are run, especially during performance of frequent and complex antiviral tasks. Examples of such tasks are checking hard disk for malware, which significantly loads computer's disk system. The consumption of processing resources by antivirus application especially affects personal computers, notebooks and other types of computers that have limited processing capabilities.
Accordingly, there is a need to improve efficiency of operation of antivirus software.